Cyber-physical additive manufacturing systems have a tight integration between cyber and physical domains. This results in new cross-domain vulnerabilities that pose unique security challenges. One of the challenges is preventing confidentiality breach due to physical-to-cyber domain attacks, where attackers can analyze various analog emissions from the side-channels to steal the cyber-domain information. This information theft is based on the idea that an attacker can accurately estimate the relation between the analog emissions (acoustics, power, electromagnetic emissions, etc.) and the cyber-domain data (such as G-code). To obstruct this estimation process, it is crucial to quantize the relation between the analog emissions and the cyber-data, and use it as a metric to generate computer aided manufacturing tools, such as slicing and tool-path generation algorithms, that are aware of these information leakage through the side-channels.
In order to tackle this inevitable security issue of confidentiality breach in cyber-physical AM systems, researchers have focused on various security solutions. Some of the solutions involved are encryption and decryption of the cyber-data being sent to the manufacturer, watermarking of the 3D object and the manufacturing process, etc. Most of the research work in the art is focused on protecting the intellectual property (“IP”) of the product after it has been built. However, there remains a presence of a persistent threat to the confidentiality of the system during the manufacturing process as well. Maintaining confidentiality during the manufacturing process might be more crucial due to the fact that these AM systems are extensively used for rapid-prototyping, and information leaked during this stage can cause the company to permanently lose its IP. In addition, researchers have recently shown that acoustic emissions from an AM system, such as 3D printers, reveal various design parameters of the 3D objects they produce. Therefore, it is imperative to analyze various analog emissions from different side-channels (such as acoustics, power, electromagnetic, etc.), and protect the system from physical-to-cyber-domain attacks during the manufacturing process.
It has been well established that in cyber-physical systems (“CPS”), various physical components divulge information due to the observability of their physical actions. Moreover, these physical actions have the tendency to unintentionally leak information about the cyber-domain from the side-channels. Side-channels have been previously used in cryptanalysis to determine the secret key by utilizing the analog emissions leaked from the physical implementation of a cryptosystem rather than using the brute force or theoretical weakness of the algorithms. The digital process chain of additive manufacturing consists of Computer Aided Design (CAD) tools for modeling 3D objects, and Computer Aided Manufacturing (CAM) tools for converting 3D models to slices of 2D polygons, and then generating tool-path (G/M-codes) based on those 2D polygons (FIG. 8A-8B). These G/M-codes (cyber-data) are eventually converted to control signals that actuate the physical components. During actuation, mechanical and electrical energies flow through the system, and may leak the information about the G/M-codes (cyber-data).
The present invention features a system and methodology that uses mutual information as a metric to quantize the information leakage from the side-channels, and demonstrates how various design variables (such as object orientation, nozzle velocity, etc.,) can be used in an optimization algorithm to minimize the information leakage. The present methodology integrates this leakage aware algorithm to the state-of-the-art slicing and tool-path generation algorithms and achieves 24.76% average drop in the information leakage through an acoustic side-channel.
Any feature or combination of features described herein are included within the scope of the present invention provided that the features included in any such combination are not mutually inconsistent as will be apparent from the context, this specification, and the knowledge of one of ordinary skill in the art. Additional advantages and aspects of the present invention are apparent in the following detailed description and claims.